A multivariate statistical input–output model for analyzing water-carbon nexus system from multiple perspectives - Jing-Jin-Ji region

Wang, P.P.; Li, Y.P.; Huang, Gordon; Wang, S.G.

doi:10.1016/j.apenergy.2022.118560

Cited by 21 publications

(5 citation statements)

References 59 publications

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“…Hoekstra and Mekonnen [ 66 ] confirmed that the agricultural sector contributed the largest share of VWF across the world, especially in China, India, and the USA. Since the BTH region was the second-biggest traditional agricultural area in China [ 67 ], the proportion of agricultural water consumption was high in all three provinces, especially in Hebei province (VWF a average >90%)—a largely agricultural province. At the same time, the rough irrigation methods further led to a large amount of water consumption in agricultural production [ 68 ].…”

Section: Discussionmentioning

confidence: 99%

Exploring the Regional Coordination Relationship between Water Utilization and Urbanization Based on Decoupling Analysis: A Case Study of the Beijing–Tianjin–Hebei Region

Shen

Yao

2022

IJERPH

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Understanding the potential association between the urbanization process and regional water shortage/pollution is conducive to promoting the intensive utilization of local water resources. In this study, the water footprint model was used to estimate water utilization status in terms of both water quantity (virtual water footprint (VWF)) and water quality (grey water footprint (GWF)) in the Beijing–Tianjin–Hebei region (China) during 2004–2017. Their potential coordination relationship with the local urbanization process represented by the gross domestic product (GDP), population (POP), and built-up area (BA) was examined using the Tapio decoupling model. The results showed that from 2004 to 2017, (1) VWF in Beijing and Tianjin showed non-significant decreasing trends, with reductions of 1.08 × 109 and 1.56 × 109 m3, respectively, while that in Hebei showed a significant increasing trend, with an increase of 5.74 × 109 m3. This indicated a gradually increasing water demand in Hebei and decreasing demand in Beijing and Tianjin. In all three regions, the agricultural sector accounted for a relatively high proportion of VWF compared to other sectors. (2) GWF in Beijing, Tianjin, and Hebei all showed declining trends, with reductions of 2.19 × 1010, 2.32 × 1010, and 1.66 × 1011 m3, respectively, indicating considerable local water quality improvement. The domestic sector contributed as the main component of GWF in Beijing, while agriculture was the main contributor in Hebei. The major contributor in Tianjin transitioned from the domestic (before 2015) to the agricultural sector. (3) We found good coordination between VWF and GDP in all three regions, as their local economic development was no longer overly dependent on water consumption. However, the expansion of urban built-up area or population would bring about accelerated depletion of water resources. (4) GWF in the three provinces showed good coordination with GDP, POP, and BA in most years, implying that the development of urbanization no longer strongly caused the pollution of water resources. In sum, policymakers should focus on improving agricultural irrigation efficiency and residents’ awareness of water conservation, so as to gradually achieve sustainable water resource management in the BTH region.

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Section: Discussionmentioning

confidence: 99%

Exploring the Regional Coordination Relationship between Water Utilization and Urbanization Based on Decoupling Analysis: A Case Study of the Beijing–Tianjin–Hebei Region

Shen

Yao

2022

IJERPH

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“…Yin et al (2020) uses the IOA method to analyse the change of the carbon footprint of household consumption in Beijing. In the study of P. P. Wang et al (2022), IOA and multivariate statistical analysis are combined to analyse the water-carbon nexus system.…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of solar energy generation on carbon footprint: Evidence from China

Hui-qing

2023

Geological Journal

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To investigate the impact of solar energy on the carbon footprint, to find effective measures to reduce the carbon footprint and slow global warming as soon as possible, this paper takes 30 provinces in China as an example. First, the inter‐regional input–output model is used to calculate the carbon footprint of each province. Then, the panel quantile regression model is used to investigate the impact of solar energy generation on different quantiles of carbon footprint. The results show that from 2012 to 2020, China's carbon footprint is at a high level, which is not conducive to the achievement of the goal of peaking carbon dioxide emissions. The eastern region has the highest carbon footprint, followed by the western region, the central region has the lowest carbon footprint, and its carbon footprint proportion continues to decline. The increase of solar energy generation can significantly reduce the carbon footprint of high quantile location, but has no significant impact on the carbon footprint of the middle and low quantile locations. Except for the negative impact of afforestation area on carbon footprint, the others control variables are all positive. Therefore, to reduce the carbon footprint of China, it is necessary to upgrade solar technology, increase solar energy generation, reduce energy consumption per unit of GDP (Gross Domestic Product) and the share of coal consumption, strengthen forestry management and reduce reliance on private vehicles.

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“…It involves assessing the ECEs in input-output (I-O) relationships between sectors and identifying key sectors and linkage pathways [46]. The classical multiplier method (CMM) proposed by Chenery and Watanabe [47] has been widely used in the study of environmental I-O systems [48][49][50][51]. However, it has been argued that CMM ignores the indirect impact of carbon emissions caused by intersectoral size disparities and that the intensity of inter-sectoral carbon transfers may be misestimated [22,52].…”

Section: Literature Reviewmentioning

confidence: 99%

Analyzing the Differences in the Quantitative and Spatial Characteristics of Inter-Provincial Embodied Carbon Transfers in China Induced via Various Demand Factors

Li,

Chen

2023

Energies

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The development of human society has led to the growing consumption of industrial products, which generates significant amounts of carbon emissions. However, relatively few in-depth studies have been conducted on the influence of different demand factors (e.g., household consumption, government consumption, export, and capital formation) on carbon emissions, which hinders the development of targeted industrial policies. To address this issue, an analytical framework based on input–output theory, the hypothesis extraction method, and complex network analysis was established to estimate the intrinsic influence of different demand factors on the embodied carbon transfer between provinces in China. The key findings can be summed up as follows: (1) The macro direction of China’s embodied carbon transfer runs from resource-rich northern provinces to industrially developed southern provinces. (2) From the perspective of different demand factors, capital formation is the most significant contributor to China’s embodied carbon transfer, with the construction industry being the most important driver. In contrast, government consumption causes the least embodied carbon transfer, but it has the highest average carbon emission intensity. (3) According to complex network theory, the carbon transfer networks via provinces and industries caused by exports are the most concentrated, with the manufacture of electrical machinery and electronic equipment serving as the main source of demand. In contrast, the carbon transfer network resulting from household consumption exhibits a high level of decentralization, with dominant sectors including electric power, gas and water production, and supply and other services. Based on these findings, this study is expected to contribute targeted suggestions with which provinces and industries can formulate demand-side carbon reduction policies for different demand factors, which will contribute to the achievement of “carbon peaking and carbon neutrality”.

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A multivariate statistical input–output model for analyzing water-carbon nexus system from multiple perspectives - Jing-Jin-Ji region

Cited by 21 publications

References 59 publications

Exploring the Regional Coordination Relationship between Water Utilization and Urbanization Based on Decoupling Analysis: A Case Study of the Beijing–Tianjin–Hebei Region

Exploring the Regional Coordination Relationship between Water Utilization and Urbanization Based on Decoupling Analysis: A Case Study of the Beijing–Tianjin–Hebei Region

Impact of solar energy generation on carbon footprint: Evidence from China

Analyzing the Differences in the Quantitative and Spatial Characteristics of Inter-Provincial Embodied Carbon Transfers in China Induced via Various Demand Factors

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